At a Glance
- Tasks: Design and maintain scalable data pipelines for AI/ML applications and mentor junior engineers.
- Company: Join Awin, a dynamic and inclusive tech company focused on innovation.
- Benefits: Enjoy a flexible four-day work week, remote working allowance, and extensive training opportunities.
- Why this job: Make an impact in the AI/ML field while developing your skills in a supportive environment.
- Qualifications: 5+ years in AI/ML engineering, strong cloud and data pipeline experience required.
- Other info: Diverse culture with a focus on well-being and professional growth.
The predicted salary is between 48000 - 72000 £ per year.
As a Senior Data Engineer, you will play a pivotal role in our AI/ML workstream, working closely with business teams and data scientists to design, maintain, and improve machine learning applications. Your main responsibilities will include managing existing ML workloads and building new batch and on-demand pipelines to support advanced AI/ML models. You’ll also contribute to developing Generative AI solutions and applications for the emerging Agentic Era.
You’ll collaborate with a global team to create scalable data architectures optimised for AI/ML, source and prepare high-quality data, and implement robust ETL processes. You should be comfortable working independently while driving improvements in engineering standards and best practices. As a senior member of the team, you will act as a mentor and advisor for junior engineers and take ownership as a project lead on strategic AI/ML initiatives.
Key Tasks- Design and maintain scalable data pipelines and storage systems for both agentic and traditional ML workloads.
- Productionise LLM- and agent-based workflows, ensuring reliability, observability, and performance.
- Build and maintain feature stores, vector/embedding stores, and core data assets for ML.
- Develop and manage end-to-end traditional ML pipelines: data prep, training, validation, deployment, and monitoring.
- Implement data quality checks, drift detection, and automated retraining processes.
- Optimise cost, latency, and performance across all AI/ML infrastructure.
- Collaborate with data scientists and engineers to deliver production-ready ML and AI systems.
- Ensure AI/ML systems meet governance, security, and compliance requirements.
- Mentor teams and drive innovation across both agentic and classical ML engineering practices.
- Participate in team meetings and contribute to project planning and strategy discussions.
- Bachelor or Master’s degree in data science, data engineering, Computer Science with focus on math and statistics / Master’s degree is preferred.
- At least 5 years experience as AI/ML data engineer undertaking above tasks and accountabilities.
- Strong foundation in computer science principles and statistical methods.
- Strong experience with cloud technology (AWS or Azure).
- Strong experience with creation of data ingestion pipeline and ET process.
- Strong knowledge of big data tools such as Spark, Databricks and Python.
- Strong understanding of common machine learning techniques and frameworks (e.g. mlflow).
- Strong knowledge of Natural Language Processing (NLP) concepts.
- Strong knowledge of scrum practices and agile mindset.
- Strong Analytical and Problem-Solving Skills with attention to data quality and accuracy.
- Clear Communication of technical concepts and effective collaboration across teams.
- Adaptability to New Technologies and a proactive approach to learning and growth.
- Team-Oriented Mindset, working closely with data scientists, AI engineers, and cross-functional teams.
- Openness to Feedback and collective problem-solving for continuous improvement.
- Team player, willing to improve yourself.
- Flexi-Week and Work-Life Balance: We prioritise your mental health and well-being, offering you a flexible four-day Flexi-Week at full pay and with no reduction to your annual holiday allowance. We also offer a variety of different paid special leaves as well as volunteer days.
- Remote Working Allowance: You will receive a monthly allowance to cover part of your running costs. In addition, we will support you in setting up your remote workspace appropriately.
- Pension: Awin offers access to an additional pension insurance to all employees in Germany.
- Flexi-Office: We offer an international culture and flexibility through our Flexi-Office and hybrid/remote work possibilities to work across Awin regions.
- Development: We’ve built our extensive training suite Awin Academy to cover a wide range of skills that nurture you professionally and personally, with trainings conveniently packaged together to support your overall development.
- Appreciation: Thank and reward colleagues by sending them a voucher through our peer-to-peer program.
Established in 2000, Awin is proud of our dynamic, social and inclusive culture. Diversity & Inclusion are paramount to us, and we proudly pursue and hire diverse team members. We champion uniqueness and authenticity; this is who we are at our core. Our network of affiliate partnerships are diverse and transparent, as are the employees powering our vision to build the world’s leading open partner ecosystem. We welcome all backgrounds, identities, and experiences. If you need support at any point in the application or interview process, please let us know.
Senior Data Scientist & ML Engineer (f/m/d) in London employer: Awin
Contact Detail:
Awin Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist & ML Engineer (f/m/d) in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage in online forums. The more people you know, the better your chances of landing that Senior Data Scientist & ML Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI/ML. This will give potential employers a taste of what you can do and set you apart from the competition.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and case studies relevant to data engineering and machine learning. Practice explaining your thought process clearly, as communication is key in this field.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior Data Scientist & ML Engineer (f/m/d) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Data Scientist & ML Engineer role. Highlight your experience with AI/ML, data pipelines, and any relevant projects that showcase your skills. We want to see how you fit into our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI/ML and how your background aligns with our mission at StudySmarter. Keep it engaging and personal – we love a good story!
Showcase Your Technical Skills: Don’t forget to highlight your technical expertise in cloud technologies, big data tools, and machine learning frameworks. We’re looking for someone who can hit the ground running, so make sure we see your strengths clearly.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, we love seeing applications come in through our own platform!
How to prepare for a job interview at Awin
✨Know Your ML Stuff
Make sure you brush up on your machine learning techniques and frameworks, especially those mentioned in the job description like mlflow. Be ready to discuss your experience with data pipelines, ETL processes, and any generative AI solutions you've worked on.
✨Showcase Your Collaboration Skills
Since this role involves working closely with data scientists and engineers, be prepared to share examples of how you've successfully collaborated in the past. Highlight your communication skills and how you’ve contributed to team projects or mentored junior engineers.
✨Demonstrate Problem-Solving Abilities
Prepare to discuss specific challenges you've faced in previous roles and how you tackled them. Use the STAR method (Situation, Task, Action, Result) to structure your answers, focusing on your analytical skills and attention to data quality.
✨Be Ready for Technical Questions
Expect some technical questions related to cloud technologies like AWS or Azure, as well as big data tools such as Spark and Databricks. Brush up on your knowledge of natural language processing concepts and be ready to explain how you've applied these in real-world scenarios.